Nonlinear Learning Control Of Robot Manipulators Without Requiring Acceleration Measurement

    Authors

    Z. H. Qu;H. Q. Zhuang

    Comments

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    Abbreviated Journal Title

    Int. J. Adapt. Control Signal Process.

    Keywords

    Learning Control; Iterative Method; Trajectory Control; Robust Control; Law; Automation & Control Systems; Engineering, Electrical & Electronic

    Abstract

    A new class of non-linear learning control laws is introduced for a robot manipulator to track a given trajectory in performing a series of tasks. The learning control scheme is applicable to robots with both resolute and prismatic joints, requires only position and velocity feedback, and removes the acceleration measurement required by the existing results. It has been shown that under the proposed learning control the tracking errors are always guaranteed to be asymptotically stable with respect to the number of trials. The proposed control is robust in the sense that exact knowledge about the non-linear dynamics is not required except for bounding functions on the magnitudes. In addition, the new learning scheme can be used without assumptions such as repeatability of robot motion, repeatability of tasks and resetting of initial tracking errors.

    Journal Title

    International Journal of Adaptive Control and Signal Processing

    Volume

    7

    Issue/Number

    2

    Publication Date

    1-1-1993

    Document Type

    Article

    Language

    English

    First Page

    77

    Last Page

    90

    WOS Identifier

    WOS:A1993LH11000001

    ISSN

    0890-6327

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